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Reactivation of TET2 reverses vascular smooth muscle cell osteogenic differentiation and prevents medial aortic calcification

GSE294266 Mus musculus Expression profiling by high throughput sequencing 8 samples Submitted 2025/07/01 Platform GPL17021
Summary
Cardiovascular diseases often manifest with vascular calcification. Vascular calcification is an active process orchestrated by contractile vascular smooth muscle cell (VSMC) phenotypic switch to an osteoblast-like cell. Here, we identified that the DNA demethylase, Tet2 (Ten-eleven translation 2), safeguards VSMCs from transitioning into the osteogenic lineage and loss of Tet2 promotes development and progression of vascular calcification. Tet2 was among the most significantly downregulated epigenetic markers in calcified aortas. VSMC-specific loss of Tet2 promoted VSMC osteogenic differentiation and enhanced vascular calcification as evidenced histologically, molecularly, and hemodynamically. In vivo studies further indicated that Tet2 inhibits calcification-associated VSMC apoptosis and medial thinning. Notably, calcified regions were enriched in a Trem2hi (triggered receptor expressed on myeloid cells 2) macrophage subpopulation. Intervention studies using high-dose ascorbate to enhance Tet2 enzymatic activity resulted in significantly reduced medial aortic calcification and improved aortic structural integrity in mice. Ascorbate treatment in human aorta organ cultures was sufficient to reduce calcification development in diseased tissues, and restore contractile properties to the calcified aorta. This study highlights the potential clinical impact of modulating Tet2 activity in managing cardiovascular disorders associated with vascular calcification.
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Direct links to NCBI, no account and no request form: the whole study as GSE294266_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 8 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1248908 and SRA study SRP578000. Searching any of these in the dataset finder brings you back here.

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